Seminar, 10. July 2017, Sitabhra Sinha

10. July 2017, 15:15 p.m. – Monday

Ernst-Abbe-Platz 2; seminar room 3423

Cancer “Module”-omics: Analyzing the network of cancer diseases and genes reveals “movers” and “shakers” of the disease

Dr. Sitabhra Sinha
(The Institute of Mathematical Sciences, Chennai)

There has been a gradual shift in cancer research away from the study of individual molecules and of single gene mutations to an emerging consensus that it is a complex disease involving large-scale disruptions in the intra-cellular signalling network. One of the drawbacks of a systems- or network-based approach to analyzing cancer is the large number of cellular agents whose interactions need to be investigated. We have tried to solve this problem by taking a mesoscopic view of the cancer diseases-genes network, by studying its modular organization after projecting it onto two networks, one comprising only disease types and the other consisting of only genes related to one or more categories of cancer. Using community partitioning method we have identified several modules in these networks.
Projecting the cancer gene clusters onto an abstract “modular space” allows us to infer relations between different tumor types. By classifying the functional role of particular genes in terms of their inter- and intra-modular connectivity, we have identified a number of genes that play the key role of “connector hubs” in the network. Using data from the human protein-protein interaction network we show that genes which are “connector hubs” or “global hubs” are in fact much more likely to be related to cancer than other genes. More important from a therapeutic point of view, we show that the connector hubs in the cancer gene network are involved in significantly larger number of human signaling pathways associated with cancer than other types of cancer genes. Furthermore, the types of cancer linked to the connector hub genes have significantly reduced survival rates compared to other types of cancer, thereby marking them as potential targets for therapy. (This work is done in collaboration with T Jesan (BARC, Kalpakkam) and Tanmay Mitra (IMSc))